A study of the vehicle scheduling problem for victim transportation

References

• Chiu , Y. C. and Zheng , H. 2007 . Real-time mobilization decisions for multi-priority emergency response resources and evacuation groups: Model formulation and solution . Transportation Research Part E: Logistics and Transportation Review , 43 : 710 – 736 .
   Google Scholar
• Chui , J. , Shi , A. and Na , C. 2010 . Regional evacuation dynamic traffic allocation based on the cell transmission model . Journal of Harbin Institute of Technology , 42 : 123 – 127 . [in Chinese]
   Google Scholar
• Cova , T. J. and Johnson , J. P. 2003 . A network flow model for lane-based evacuation routing . Transportation Research Part A , 37 : 579 – 604 .
   Google Scholar
• Daganzo , F. C. 1994 . The cell transmission model: A dynamic representation of highway traffic consistent with the hydrodynamic theory . Transportation Research Part B , 28 : 269 – 287 .
   Google Scholar
• Daganzo , F. C. 1995 . The cell transmission model, part II: Network traffic . Transportation Research Part B , 29 : 79 – 93 .
   Google Scholar
• Dunn , C. E. and Newton , D. 1992 . Optimal routes in GIS and emergency planning applications . Area , 24 : 259 – 267 .
   Web of Science ®Google Scholar
• Hamza-Lup , G. L. , Hua , K. A. and Peng , R. 2007 . Leveraging e-transportation in real-time traffic evacuation management . Electronic Commerce Research and Applications , 6 : 413 – 424 .
   Web of Science ®Google Scholar
• Jia , B. , Gao , Z. Y. , Li , K. P. and Li , X. G. 2007 . Models and simulations of traffic system based on theory of cellular automaton , Beijing : Science Press [in Chinese] .
   Google Scholar
• Kim , S. , Shekhar , S. and Min , M. 2008 . Contraflow transportation network reconfiguration for evacuation route planning . IEEE Transactions on Knowledge and Data Engineering , 20 : 1115 – 1129 .
   Web of Science ®Google Scholar
• Meng , Q. , Khoo , H. L. and Cheu , R. L. 2008 . Microscopic traffic simulation model-based optimization approach for the contraflow lane configuration problem . Journal of Transportation Engineering , 134 : 41 – 49 .
   Web of Science ®Google Scholar
• Ng , M. W. and Waller , S. T. 2010 . Reliable evacuation planning via demand inflation and supply deflation . Transportation Research Part E: Logistics and Transportation Review , 46 : 1086 – 1094 .
   Web of Science ®Google Scholar
• Sattayhatewa, P., & Ran, B. (2000). Developing a dynamic traffic management model for nuclear power plant evacuation. Paper presented at the 79th annual meeting of the Transportation Research Board, Washington, DC
   Google Scholar
• Urbanik , T. 2000 . Evacuation time estimates for nuclear power plants . Journal of Hazardous Materials , 5 : 165 – 180 .
   Google Scholar
• Urbina , E. and Wolshon , B. 2003 . National review of hurricane evacuation plans and policies: A comparison and contrast of state practices . Transportation Research Part A , 37 : 257 – 275 .
   Google Scholar
• Waller , S. T. and Ziliaskopoulos , A. K. 2006 . A chance constrained based stochastic dynamic traffic assignment model: Analysis formulation and solution algorithms . Transportation Research Part C: Emerging Technologies , 14 : 418 – 427 .
   Web of Science ®Google Scholar
• Xie , C. , Lin , D. Y. and Waller , S. T. 2010 . A dynamic evacuation network optimization problem with lane reversal and crossing elimination strategies . Transportation Research Part E: Logistics and Transportation Review , 46 : 295 – 316 .
   Web of Science ®Google Scholar
• Yang , Z. S. , Gao , X. Y. and Sun , D. 2011 . Cell automata model of urban traffic emergency evacuation and rescue . Journal of Traffic and Transportation Engineering , 11 : 114 – 120 . [in Chinese]
   Google Scholar
• Zhou , L. , Ren , A. and Zhang , X. 2006 . GIS-based disaster evacuation simulation and rescue dispatch in disaster . Journal of Natural Disasters , 15 : 141 – 145 . [in Chinese]
   Google Scholar
• Ziliaskopoulos , A. K. 2000 . A linear programming model for the single destination system optimum dynamic traffic assignment problem . Transportation Science , 34 : 37 – 49 .
   Web of Science ®Google Scholar